Nathan R. Sturtevant
Fellow, Canada CIFAR AI Chair & Interim Director
Academic Affiliations
Areas of Expertise
Fellow, Canada CIFAR AI Chair & Interim Director
Academic Affiliations
Areas of Expertise
Nathan Sturtevant’s research looks broadly at heuristic and combinatorial search problems, including both theoretical and applied approaches.
Nathan Sturtevant’s research looks broadly at heuristic and combinatorial search problems, including both theoretical and applied approaches. His work focuses on heuristic and combinatorial search for single and multiple agents including bidirectional search, cooperative search, large-scale and parallel search, search for game design, heuristic learning, automated abstraction for building heuristics, refinement search, and inconsistent heuristics. His teams also work on methods for combining search with machine learning. Particular applications for Nathan’s research include pathfinding and planning in memory-constrained real-time environments (e.g. commercial video games) as well as algorithms for building and using memory-based heuristics via large-scale search. Other work considers theoretical and practical issues in games with more than two players, including opponent modelling, learning, and imperfect information. His research has been implemented in commercial video games and he continues to collaborate with practitioners in the games industry.
Nathan is a Professor in the Department of Computing Science at the University of Alberta and a Canada CIFAR AI Chair and Fellow at Amii. He is the interim director of Amii at the University of Alberta and holds a joint appointment as a Research Professor at the University of Denver. He also leads the Moving AI Lab, which has students both at the University of Alberta and the University of Denver. Nathan is a senior member of the Association for the Advancement of Artificial Intelligence, Associate Editor for the Journal of Artificial Intelligence Research and sits on the Editorial Board for the Artificial Intelligence Journal. Papers co-authored by Nathan have received awards and accolades at top conferences, including the Artificial Intelligence and Interactive Digital Entertainment (AIIDE), the International Symposium on Combinatorial Search (SoCS), and the Association for the Advancement of Artificial Intelligence (AAAI) Annual Conference.
Nathan is a senior member of the Association for the Advancement of Artificial Intelligence, Associate Editor for the Journal of Artificial Intelligence Research and sits on the Editorial Board for the Artificial Intelligence Journal.
Oct 1st 2020
Research Post
Human designers may find it difficult to anticipate the impact of small changes to some games, particularly in puzzle games. However, it is not difficult for computers to simulate all mechanical impacts of such small changes. This suggests that computers might be able to aid humans designers as they build and analyze game levels.
Jun 1st 2020
Research Post
Jun 1st 2020
Research Post
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